Advanced Observability: Real-World Monitoring And Logging

Master observability with hands-on projects, real-world scenarios, and job-ready skills for SREs, DevOps, and Cloud.

What you'll learn

Build a complete Observability Stack using open-source tools – deploy and integrate Prometheus for metrics, Grafana/Loki for logs

Live Labs from Scratch: Follow along with live lab setups built from the ground up. With access to a cloud account, you can replicate every environment and expe

Diagnose real production issues with observability data – practice troubleshooting latency, errors, and failures in complex systems by correlating logs, metrics

Design Service Level Objectives (SLOs) and Alerts – define reliability targets (SLO/Error Budgets) and configure alerting rules that inform you of problems.

Implement Observability in Cloud & Kubernetes environments – monitor containerized applications, use Kubernetes event logs and metrics, and deploy in k8s

Best Practices & Performance Tuning – learn advanced tips (optimizing logging levels, handling high-cardinality metrics, and minimizing observability overhead)

Requirements

Basic Knowledge of DevOps & Containers: Familiarity with Docker and fundamental DevOps concepts will help in understanding the deployment of observability tools

General Cloud Understanding: Experience with any cloud provider (AWS, Azure, GCP) is recommended. You should have access to a free-tier or personal cloud account for optional cloud-based lab exercises

Linux Command Line Basics: Ability to navigate and run simple commands on a Linux terminal is needed, since many tools are deployed on Linux or via Docker.

Prior Monitoring/Logging Exposure (Optional): Basic experience with monitoring or logging (even at a beginner level) will be beneficial but not strictly required – we will recap the fundamentals before diving deep.

Hardware/Software: A computer (Windows/Mac/Linux) capable of running multiple Docker containers for labs, and an internet connection. We will use free/open-source software throughout the course.

Eagerness to Learn by Doing: A willingness to set up environments, experiment with configurations, and troubleshoot will greatly enhance your learning experience in this hands-on course.

Description

Observability is more than a buzzword – it's a critical skill set for today’s SREs and DevOps engineers. “Advanced Observability” is a project-based course that goes beyond theory, immersing you in real-world scenarios. In this course, you will build and break things on purpose: instrument applications with telemetry, set up a full observability stack, and troubleshoot complex systems just as you would on the job. Our approach is formal in coverage yet slightly conversational in tone, making advanced concepts accessible and engaging.Throughout the course, we emphasize learning by doing. Each module centers around a realistic project or problem scenario – from debugging a microservices outage to optimizing performance in a live environment. You won't just learn definitions or passively watch tool demos; you'll actively implement logs and metrics in a hands-on lab environment. By working through guided labs and challenges, you’ll gain confidence using industry-standard tools (like Prometheus, Grafana, Loki etc) and tie them together into a cohesive observability platform.By the end of this course, you’ll have job-ready observability expertise. You will know how to proactively monitor distributed systems, quickly pinpoint issues across complex architectures, and improve reliability using data-driven insights. Whether you’re aiming to excel in an SRE/DevOps role or to bring observability best practices to your team, this course delivers practical experience that translates directly to real-world success. Get ready to elevate your skills through immersive projects and become an observability champion in your organization!

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Getting Started with Observability

Lecture 2 01. Observability in Distributed Environments

Lecture 3 02. Prometheus Architecture

Lecture 4 03. Setting up and Configuring Prometheus

Lecture 5 04. Monitoring an External Machine

Lecture 6 05. Q&A

Section 3: Collecting Node data Using Exporters (Node Exporter)

Lecture 7 06. Summary - Setting up Nginx and Node Exporter

Lecture 8 07. nginx exporter

Lecture 9 08. Default Labels

Section 4: Visualising the Data using Grafana Dashboards

Lecture 10 09. Visualizing the Data in Prometheus

Lecture 11 10. Setting Up and Configuring Grafana

Lecture 12 11. Creating Dashboards in Grafana

Lecture 13 12. Adding Memory Panels to Grafana Dashboards

Section 5: Grafana Dashboards Advanced Topics

Lecture 14 13. Grafana Dashboard Library

Lecture 15 14. Managing Dashboards like Code

Section 6: Generating Metrices on your Nodes

Lecture 16 15. Generating metrices

Lecture 17 16. Push gateways

Lecture 18 17. Grafana Dynamic Dashboards and Variables

Section 7: Prometheus Stack on Kubernetes

Lecture 19 18. Running Prometheus on Kubernetes

Lecture 20 19. Running Prometheus on Kubernetes - The Right Way

Lecture 21 20. Install Prometheus Helm Package

Lecture 22 21. Configuring installed components

Lecture 23 22. Accessing the kubernetes services locally

Lecture 24 23. Default Monitoring Configurations

Section 8: Monitoring Your Custom Applications on Kubernetes

Lecture 25 24. Monitoring Your Custom Applications

Lecture 26 25. Prometheus Rules

Section 9: SLI, SLO, SLA

Lecture 27 26. SLI SLO SLA

Lecture 28 27. Using Sloth for generating SLO based rules

Lecture 29 28. Applying and visualizing the SLO based rules

Lecture 30 29. Best Practices

Section 10: Advanced hands on Logging practices Grafana Loki

Lecture 31 30. Grafana Loki

Section 11: The Final Project

Lecture 32 30. Project

Site Reliability Engineers (SREs) who want to master the art of observability and take their incident response skills to the next level.,DevOps Engineers aiming to implement comprehensive monitoring and tracing in CI/CD pipelines and production systems.,Software Developers who wish to understand what happens to their code in production and how to instrument applications for better debuggability.,System Administrators & IT Operations staff looking to proactively detect and resolve infrastructure issues using logs, metrics, and alerts.,Technical Support Engineers who troubleshoot production issues and need deeper insight into system behavior to resolve customer problems faster.,QA and Test Engineers interested in observing system performance and reliability during testing, and learning how to use observability data to validate features under load.,Cloud Architects/Engineers designing modern microservices or cloud-native architectures, who need to embed observability for distributed systems at scale.,Enthusiastic Learners who have basic ops/dev experience and are eager to step into an SRE, DevOps, or reliability-focused role by acquiring in-demand observability skills.